The invention relates to volume rendering, in particular to multi-planar reformatting (MPR) using a computer system that includes a graphics processing unit (GPU).
Volume rendering is the standard visualization method for viewing two-dimensional (2D) representations of three-dimensional (3D) data sets and is widely used in medical imaging. MPR volume rendering is a standard rendering method for processing 3D data sets collected by medical imaging equipment, such as computer-assisted tomography (CT) scanners, magnetic resonance (MR) scanners, ultrasound scanners and positron-emission-tomography (PET) systems. These 3D data sets are sometimes referred to as volume data. General background on volume rendering can be found in the text book Lichtenbelt, B., Crane, R. and Naqvi, S., “Introduction to Volume Rendering”, Hewlett-Packard Company, Prentice-Hall PTR, New Jersey, 1998 [1].
Medical image data sets are generally large. Sizes of between 0.5 Gigabytes and 8 Gigabytes are not uncommon. For example, a medical image data set might comprise 1024×1024×1024 16-bit voxels which corresponds to approximately 2 Gigabytes of data. From this an image comprising 1024×1024 16-bit pixels might be rendered.
Current CT scanners are being developed to allow so-called four-dimensional (4D) imaging, where the fourth dimension is time. In other words, the CT scanners are providing 3D images as a function of time. The goal is to allow real-time viewing in 3D. Imaging of the heart, cardiology, is an important application, where it is desired to view the beating heart of a patient. Current state of the art CT scanners are not able to record a full cycle of the heart in one take. Instead, different phases of the heart beat are recorded in different beats, and the images stitched together, for example out of 3 or 4 different heart beats, to give the impression of imaging in real time. Within the next few years CT scanners are expected to become commercially available that will allow a full single beat of the heart to be acquired in one take. This will be made possible through the use of dual source CT scanners and scanners that increase from the present 64 slice standard to 256 slices. The rendered images to be viewed by a user as a movie or cine typically need a frame rate of at least 10 frames per second (fps), preferably 20 or 30. It is also preferable if cines can be generated and displayed in real time. Similar developments are taking place in MR scanners and also ultrasound and other scanner types.
With these great advances in machine capability, advances in the rendering is also required. Specifically, while the heart is undoubtedly one of the most important organs to visualize in 4D so that its complex motions can be studied by a clinician, these complex motions present particular challenges for the rendering. The vigorous motion of the heart induced by its beating causes it to move around inside the patients body and also dilate (diastole) and contract (systole). A rendered image of a 4D) CT scan can thus be indistinct and of only limited use to a clinician.
Some work has been done in numeric processing of 3D images to enable automatic identification and characterization of principal heart features, in particular aortic and mitral valves.
EP 1 832 233 A1 [2] discloses a method for processing 3D echochardiac, i.e. ultrasound, data in order to measure performance characteristics of a mitral valve. The method uses a replica exchange and simulated annealing techniques, but is based on an initial manual identification by a user of the positions of the mitral valve annulus and leaflets on each individual data slices before processing can take place.
US 2005/0281447 A1 [3] relates to 3D imaging and provides a computationally efficient method of finding the location of an aortic valve from a CT volume data set. A slice is taken through the aorta, and the aorta located in the slice. The aorta is then followed down towards the aortic valve, the position of which is detected by a sudden reduction in the measured diameter of the aorta.
JP 2002-140690 [4] discloses an automated method for examining a heart valve that can be applied to ultrasound, CT or other volume data sets. The valve shape is determined from the 3D image using an doughnut-shaped search shape which is multiply axially sectioned. The method is extended to 4D to allow the speed of motion, and acceleration, of the valve to be quantified, these dynamic data being useful for diagnosis. While this method extends to 4D, from what can be understood from the Japanese Patent Office machine translation into English, it does not involve any 4D rendering, rather only analysis of the change in position of the doughnut-like geometrical construct over time.
It appears from our searching that there is still a general lack of available methods and associated apparatus to allow high quality volume rendering in 4D of the heart, and in particular heart valves.